Richer color vocabulary is associated with better color memory but not color perception

The potential interaction between color naming and psychophysical color recognition has been historically debated. To study this interaction, here we utilized two approaches based on individual differences in color naming and variation of color name density along the color wheel. We tested a pool of Persian speaking subjects with a simple color matching task under two conditions: perceptual and memory-based matching. We also asked subjects to freely name 100 evenly sampled hues along the color wheel. We found that, individuals who possess more names to describe the color wheel have a strong edge in color memorization over those with fewer names. Nevertheless, having more or fewer color names was not related to the subjects’ performance in perceptual color matching. We also calculated the density of color names along the color wheel and observed that parts of the color wheel with higher density of color names are held in memory more accurately. However, similar to the case of individual differences, the density of color names along the wheel did not show any correlation with perceptual color matching performance. Our results demonstrate a strong link between color naming and color memorization both across different individuals and different parts of the color wheel. These results also show that low-level perceptual color matching is not related to color naming, suggesting that the variation in color naming—among the individuals and across the color wheel—is neither the cause nor the effect of variation in low-level color perception.

Humans break the color wheel into smaller segments, each labeled by a color name. Some individuals employ more names to segment the color wheel and some, less sophisticated with naming, use fewer labels to describe it. Do individuals who possess more color names have better color vision? For nearly half a century, considerable debates have been raised over this simple question. On one hand, the “universalist view” suggests that the mental process of color recognition is independent of the linguistic processes that assign names to colors. According to this view, the linguistic color pallet, the vocabulary treasure that discriminates various hues in a language, does not constrain the way humans perceive and remember colors (1, 2). On the other hand, the “relativist view” implies that assignment of color names to various parts of the color wheel interacts with color recognition performance in humans (3–10).To address the debate between universalist and relativist views, one should experimentally address a “problem of circularity” formalized by Winawer and Witthoft (11). The problem of circularity arises from an inherent problem in the definition of “spacing” in any color space. In order to psychophysically measure the potential effect of linguistic category boundaries on color recognition for different colors (within or between category boundaries), the experimenter first needs to create a physically controlled and evenly spaced color space. Now, if linguistic color categories are taken into account for equal spacing of test colors, then by definition there won’t be any residual linguistic effects left to measure; if not, how can one ensure the test colors were equally spaced to begin with? In the latter case, any observed category effect may reflect the possibility that colors within a linguistic category are psychophysically harder to discriminate and that’s why they have fallen into a natural category in the first place. Winawer and Witthoft have listed three categories of psychophysical approaches to break the circularity problem and investigate the potential relationship between language and color vision: cross-linguistic studies, hemifield specific effects, and verbal interference experiments.Historically most of the fuel for the debate between universalist and relativist camps come from cross-linguistic studies. In this approach, variation of linguistic color pallet across different languages is used to explain the variation in color recognition performance among the speakers of those languages (e.g., refs. 1, 2, 5, 7–10). In this way the circularity problem is bypassed because the physical spacing of test colors can be kept constant while linguistic category boundaries vary across different languages. Some cross-linguistic studies have revealed interesting effects of language on color memory and learning (e.g., refs. 5, 6, 9), thus supporting the relativist view. Nevertheless, other studies have supported the universalist view (e.g., refs. 1, 2). As informative as cross-linguistic studies are, they come with an inherent problem; cross-cultural confounding factors. Distance from the equator that determines the amount of ultraviolet (UV) damage to the eyes (12), variations in advancement and application of color display technology (13), and cultural variation in exposure to colorful materials (14) are among the many variables that affect color recognition performance and may vary across cultures besides the variation in language. In addition, other sources of variance such as individual differences in color recognition may contaminate cross-linguistic measures of color recognition performance (15). These sources of variance may conceal potential effects of language on color recognition and explain some of the discrepancies in the literature.Another category of psychophysical studies that concern language and color vision has emerged based on the neurophysiological fact that in most people, language is mostly processed by the left hemisphere (16–18). This leads to the assumption that visual stimuli that are presented to the left hemisphere (right visual field) are influenced more by language. This assumption addresses the circularity problem by keeping the physical spacing of colors constant, yet varying the linguistic effects by varying the visual field. These experiments are done in the context of a single language (19, 20) as well as in combination with cross-linguistic studies (21). The latter case is quite interesting because it controls for potential cross-linguistic confounding factors. In some cases, this category of experiments has revealed effects of linguistic category boundaries on color recognition in the context of speeded visual search task (e.g., refs. 19–21). However, other studies have failed to replicate some of those results and the source of discrepancy is still debated (22, 23).The third category of evidence comes from verbal interference experiments. The idea behind this class of studies is that if color vision depends on language, it should be affected by the conditions in which language faculty is overloaded by a parallel task (6, 7, 10, 19). The problem of circularity is addressed here by keeping the spacing between colors physically constant, and varying the involvement of the language faculty in the task. These experiments are done both for a single language (e.g., refs. 6, 19) and in the context of cross-linguistic studies (e.g., refs. 3, 7, 10). Verbal interference experiments generally support the relativist view as they reveal various effects of verbal interference on color visual search (19), speeded color matching reaction times (7, 10), color memory (6), and oddball color detection (3). The problem with verbal interference experiments is rather a pragmatic one. Given the difficulty of performing interference experiments for human subjects, the number of verbal interference trials that can be collected from each subject is small and practically limited to the median of 96 trials (ranged from 432 to 16) in the previous studies (e.g., refs. 6, 7, 10, 19). Because of this limitation, the entire body of evidence in this category comes from a carefully selected but limited set of colors around specific linguistic category boundaries such as the blue/green (e.g., refs. 3, 6, 19, 24) blue/dark-blue (e.g., refs. 7, 10) boundaries and multiple (seven) preselected category boundaries (25). The generality of these findings for the entire color wheel is yet to be studied. Building on this rich history, here we introduce two approaches in order to eliminate some of the limitations of previous studies and to investigate the interaction of language with color recognition more directly. In the first approach, in order to avoid cross-cultural confounding factors, we utilized individual differences in color naming and color recognition within only one linguistic domain. There are individual differences in color naming and color recognition even within a language domain (9, 26, 27); we harnessed this natural variance in order to study the covariance of color naming and color recognition in a pool of Persian speaking subjects. Here, to break the problem of circularity, we kept the physical colors constant and varied the observer within a cultural domain.In the second approach, unlike many previous studies that were limited only to specific color category boundaries, here we measured the subjects’ color naming and color recognition performance for the entire color wheel in a parameterized way. Then, we used heterogeneity of distribution of color names and color recognition performance along the color wheel as a source of variance to study their relationship. In this approach, instead of trying to neutralize the problem of circularity, we directly measured its effects on a physically constant set of colors in the context of two different psychophysical tasks; perceptual and memory-based matching (Discussion). The analytical methods developed here are language independent, thus they can be replicated and compared for any other language domain in the future.To measure color recognition performance we adopted two separate operational definitions of “color recognition”: a simple low-level color matching task to directly assess concurrent color perception of the subjects, as well as a color memory task. Using these two tasks we aimed at two empirical questions: 1) Is color perception and color memory performance different among individuals with different vocabulary treasure of color names? 2) Independent of individual differences, does the distribution of color names along the color wheel predict color recognition performance for different hues?To achieve these aims, we tested color recognition abilities of the subjects using a color matching paradigm. In each trial, the subjects were required to change the color of a “test patch” on the screen to match it with that of a “reference patch.” The reference patch was filled randomly with one of the 100 hues evenly sampled from an imaginary circle in the CIEIUV color space (Methods). There were two conditions for this task: the “perceptual matching” condition and the “memory-based matching” condition. In the perceptual matching condition, a test patch and a reference patch were presented simultaneously and the subjects could look at the reference patch as they made their match. This task aimed at documenting the most basic color recognition abilities of the subjects. In the memory-based matching condition, the reference patch was shown for 10 s, then it disappeared; following a delay of 10 s the test patch was presented to the subjects who matched its color to their memory of the reference patch. This task is tailored to measure color memory performance for each sampled hue separately (Fig. 1).Open in a separate windowFig. 1.(A) Stimuli. One hundred hue samples were selected evenly from the perimeter of an imaginary circle (r = 0.08) centered at gray in CIELUV color space. The color wheel on the Right side of the panel shows the sampled hues, U and V values varied among the 100 sampled colors but the luminance level was kept constant at 1 cd/m². (B) Color matching experiment in two conditions: perceptual matching and memory-based matching. Participants used a computer screen to match the color of 100 hue samples (presented in random order) under two conditions. In perceptual matching condition (Top) two patches of color were presented simultaneously on a black background. In each trial, one of the 100 sample colors, randomly selected, was presented in the top color patch (reference patch). The participants adjusted the color of the bottom patch (test patch) to match it with the reference patch. For each trial, the participants had 60 s to complete the matching procedure. Memory-based matching (Bottom) was similar to perceptual matching except for a 10-s delay introduced between the reference and test patches. In this condition, the participants were asked to withhold the color of the reference patch in memory and adjust the color of the test patch to match the memorized hue (see text for details). (C) Color matching results in a typical subject. The radius of each data point shows the average error of the matches for the 100 color samples. The blue line corresponds to perceptual matching and the red line represents memory-based matching.To determine the linguistic color pallet of each subject for the sampled color wheel, all of the subjects participated in a separate color naming task (Fig. 2A). The color naming task was presented to subjects after they completed the other two tasks; this was done to avoid potential biases in subjects’ performance in the two other tasks by informing them about our interest in language. In the color naming task the subjects were presented with all 100 sampled hues, one at a time in random order, and asked to type the name of the hue in a dialogue box. At first glance we measured the total number of names that each subject possesses to describe the entire perimeter of the sampled color wheel. The linguistic color pallets of our 20 subjects contained 21 to 50 unique names (mean = 38.80, SD = 7.709) for the tested colors. Female and male subjects possessed an average of 36.14 (median = 38) and 40.23 (median = 41) total color names, respectively. The effect of gender on the number of color names was not significant (t test, t (18) = 1.14, P = 0.2692). Then we investigated the relationship between subjects’ performance in the color matching task and the total name count on their color pallets. The distance between the reference hue and matched hue was defined as “error” for each match. For each subject, this error was averaged across all trials. We noticed a strikingly strong correlation between error and total color name count across subjects for memory-based color matching (r = −0.9428, P < 0.00001); the more color names you possess the better your color memory is (Fig. 2B). However, the clear advantage of people with more color names in the color memory task cannot be the result of their better color perception, simply because there was no correlation between error and total color name count for the perceptual color matching condition (r = −0.1462, P = 0.53).Open in a separate windowFig. 2.The more names an individual uses to describe colors the better her/his performance is on a color memory matching test. (A) Color naming task. All of the 100 sampled hues were presented to the subjects in random order in separate trials. In each trial, subjects were asked to type the name of the presented color into a text box on the screen (in Persian). (B) The abscissa indicates the number of unique names that each subject has to describe the color wheel. The ordinate represents the error (average of 20 subjects) of the participants on the color matching experiment. Each data point represents one of the 20 participants. While individuals who possess more names to describe the color wheel are similar to others in color perception, they can memorize colors more accurately. Left and Right, respectively, represent perceptual (r = −0.146, P = 0.538) and memory-based (r = −0.942, P < 0.0001) matching conditions. Upper subpanels depict color naming schema of two of the subjects (the ones who had the least and most color names). Each sector on the color wheel corresponds to a unique name that the subject uses to describe that part of the wheel.Did the subjects explicitly memorize the names of colors to perform the memory-based color matching task? Such an internal naming strategy may have helped the subjects who possess more color names in the memory-based task, thus it can explain the strong correlation observed. In order to assess the potential role of internal color naming in the subjects’ strategy for performing the color memorization task, in an exit interview we asked the participants to describe the strategy they used to remember different colors. Eight of the 20 participants (40%) reported that they memorized the exact test hues and not their names. For this group of subjects correlation between the size of color vocabulary and memory error was high and significant (r = −0.9620, P = 0.0001). The remaining 12 subjects (60%) reported that they matched the colors by memorizing both the hues and the hue labels. A similar near perfect correlation was observed for this group (r = −0.9538, P = 0). Fisher Z test shows no significant difference between these two correlation values (z = −0.2, P = 0.41). This suggests that the link between language and color memory is as strong for those subjects who “consciously and explicitly” think they have not used internal naming to perform the task (SI Appendix, Fig. S1). It is still possible that those subjects used some form of linguistic labeling without being consciously aware of it; we do not intend to reject this theoretical possibility and we leave its further exploration to future studies. In fact, if a form of implicit linguistic labeling mechanism exists, we would classify it as a natural mechanism for color memorization, given that we provided no instructions for performing our task. In any case, here, we only conclude that explicit usage of internal naming for performing memory-based color matching does not affect the correlation between color memory and color vocabulary size.Next, we aimed at our second empirical question: Is the distribution of color names along the wheel related to color recognition performance for various hues? To create a quantitative and language-independent measure of the distribution of color names we defined “name density.” Name density is the number of unique names that subjects possess to describe a small section of the color wheel. To measure name density for all hues, a sliding window (±5 hues from each sampled hue) was moved along the 100 sampled hues for each subject and the number of unique color names in each window (11 hues wide) was counted. As a result, a name densitogram was created for each subject. The name densitogram indicates the number of unique names that each subject has for each part of the tested color wheel (Fig. 3A).Open in a separate windowFig. 3.Variation of color name density and color matching performance along the color wheel. (A) Name densitogram. Name density (ND) was defined as the number of names that an individual assigned to each subsection of the color spectrum. The name densitogram shows the density of unique names at each point on the tested color spectrum for each individual (see text for details). (B) Interaction of name density and performance in color matching experiment. Black line indicates ND. Blue and red lines show error (average of 20 subjects) of the matches for the 100 tested hues in perceptual and memory-based matching, respectively. Vertical and horizontal axis labels correspond to error and name density, respectively.First, we noticed that name density varies significantly in different parts of the color wheel. In general, Persian speaking subjects have fewer names for orange (mean = 2.8) and purple (mean = 3.38) tones and more names for pink (mean = 6.8), and blue (mean: 4.7) and light green (mean = 5.12) shades. Among the pool of subjects one-way ANOVA showed a significant effect of hue on name density for all subjects (F (19,99) = 26.30, P < 0.000001). Analysis of data from individual subjects showed a significant negative correlation between name density and color matching error (across all hues) for the memory-based matching task in 16 out of 20 subjects. The distribution of Pearson r values among subjects was significantly below zero for memory-based matching (mean r = −0.321, SD = 0.189, t test: t (19) = −7.59, P < 0.00001). Name density and color matching error showed significant correlations only in 2 of the 20 subjects for the perceptual matching condition. The distribution of r values was not significantly different from zero for perceptual matching (mean r = −0.0478, SD = 0.138, t test: t (19) = −1.54, P = 0.07).We also averaged the data across all individuals and calculated average error and name density for each hue (Fig. 4). Average name density and average error (both pooled across all subjects) showed a significant negative correlation for memory-based matching (r = −0.555, P < 0.00001) and not for perceptual matching (r = −0.05, P = 0.609). To make sure the effects observed in the memory condition have not originated from any low-level effect potentially present in the results of the perceptual condition, we normalized memory error values to perceptual errors for each hue and correlated them with name density (r = −0.36, P < 0.001). This normalization obviously adds noise to the correlation, but the remaining significant correlation ensures that the memory effect is not shaped by any inhomogeneity in perceptual matching across the color wheel. In sum, this analysis shows that the density of color names varies across the different parts of the color wheel, and that color memory performance is higher in subareas of the wheel that incorporates more color names. However, the density of color names along the wheel does not influence perceptual color matching performance.Open in a separate windowFig. 4.Distribution of color names over the color space is not even and color matching performance reflects it. The parts of the color wheel that are described by more names (higher name density) are remembered more accurately. The abscissa indicates the name density (ND) around each hue on the color wheel and the ordinate represents the error (average of 20 subjects). Each data point depicts one of the 100 tested hues. Left represents performance in perceptual color matching (r = −0.051, P = 0.609) and Right represents performance in memory-based color matching (r = −0.555, P < 0.0001).The method of adjustment used in this study allows variation in color matching time and this can potentially affect the results. To study the potential role of matching time in the phenomena observed here, we first explored the potential effect of matching time on color matching accuracy within the time variation range naturally present in the data. We observed no significant correlation between accuracy (inverse of the error) and matching time across the sampled hues (r = −0.013, P = 0.89) and across the individuals (r = 0.08, P = 0.73) for memory-based color matching in our data (also see SI Appendix, Fig. S2). Next, to reassure that matching time does not affect our main findings, we divided the trials into two groups based on trial matching times: fast trials (trials faster than the mean reaction time) and slow trials (trials slower than the mean reaction time). Our main effect was repeated for both trial types with no significant change in the effect size (SI Appendix, Fig. S3).     

Doppler color flow image size: dependence on instrument settings

Doppler color flow imaging provides important qualitative information about the location and spatial distribution of intracardiac blood flow. However, the effect of instrument-related variables on the size of color Doppler images requires further definition. Flow of a silicone particle solution was established in a tube or cylinder and scanned as color gain, pulse repetition frequency, depth, and transducer frequency were varied. The diameter of Doppler color flow images were measured during constant laminar or disturbed flow parallel to the ultrasound beam and during laminar flow perpendicular to the ultrasound beam. The diameter of color Doppler images of laminar flow perpendicular and parallel to the beam varied directly with color gain. Diameter varied inversely with transducer frequency for laminar flow parallel to the transducer and inversely with pulse repetition frequency for laminar flow perpendicular to the transducer. The diameter of laminar flow parallel to the transducer varied directly with the depth of the flow area below the transducer. The size of the color flow dropout of laminar flow exactly perpendicular to the ultrasound beam varied directly with transducer frequency and inversely with gain. During disturbed flow parallel to the transducer, the diameter of the image varied directly with gain and inversely with transducer frequency and pulse repetition frequency. Instrument settings have a significant impact on the size of color Doppler images. Understanding the effects of changes in these variables is important for reliable diagnostic use of Doppler color flow imaging.     

Color Kinesis: Principles of Operation and Technical Guidelines

Color kinesis is a new echocardiographic technique that aids in the assessment of global and regional left ventricular performance during either systole or diastole. Color kinesis uses automated border detection technology based on backscatter data to display both the magnitude and timing of endocardial motion in real time. The color kinesis display superimposes a color overlay on the two-dimensional echocardiographic image; the number of color pixels represents the magnitude of endocardial motion, while the different colors represent the timing of endocardial motion according to a predefined color scheme. Because color kinesis is an operator-dependent technique, the steps involved in performing a technically adequate study will be reviewed as well as the pitfalls and technical limitations. The potential clinical applications of color kinesis will also be discussed.     

Color preference in red–green dichromats

Around 2% of males have red–green dichromacy, which is a genetic disorder of color vision where one type of cone photoreceptor is missing. Here we investigate the color preferences of dichromats. We aim (i) to establish whether the systematic and reliable color preferences of normal trichromatic observers (e.g., preference maximum at blue, minimum at yellow-green) are affected by dichromacy and (ii) to test theories of color preference with a dichromatic sample. Dichromat and normal trichromat observers named and rated how much they liked saturated, light, dark, and focal colors twice. Trichromats had the expected pattern of preference. Dichromats had a reliable pattern of preference that was different to trichromats, with a preference maximum rather than minimum at yellow and a much weaker preference for blue than trichromats. Color preference was more affected in observers who lacked the cone type sensitive to long wavelengths (protanopes) than in those who lacked the cone type sensitive to medium wavelengths (deuteranopes). Trichromats’ preferences were summarized effectively in terms of cone-contrast between color and background, and yellow-blue cone-contrast could account for dichromats’ pattern of preference, with some evidence for residual red–green activity in deuteranopes’ preference. Dichromats’ color naming also could account for their color preferences, with colors named more accurately and quickly being more preferred. This relationship between color naming and preference also was present for trichromat males but not females. Overall, the findings provide novel evidence on how dichromats experience color, advance the understanding of why humans like some colors more than others, and have implications for general theories of aesthetics.Individuals vary in their perceptual experience of the world, and sometimes this variation is caused by genetic differences (1–4). Dichromacy is a form of color-vision deficiency affecting about 2% of human males in which only two of the three types of retinal cone photoreceptors are functional because of genetic factors (1, 2). Protanopes, deuteranopes, and tritanopes lack cone photoreceptors sensitive to long (L), medium (M), and short (S) wavelengths, respectively. Accordingly, dichromats’ color discrimination is poorer, and their spectral sensitivity is slightly shifted to longer wavelengths (deuteranopes) or is moderately shifted to shorter wavelengths (protanopes) compared with that of normal trichromats (common observers; see table 3.6 in ref. 5).In normal trichromats, cone responses are the input signals for two chromatic cone opponent mechanisms, red–green and yellow–blue, based on L−M and S−(L+M) cone responses, respectively, and one achromatic mechanism, mainly based on L+M responses (1). Traditionally it has been considered that protanopes and deuteranopes lack functionality in the red–green mechanism, because this opponent mechanism is based on the comparison of L and M cone responses, and one of those cone types is affected. (Thus such observers are called “red–green dichromats.”) However, research also has shown that a large proportion of red–green dichromats have residual activity in this mechanism with increasing stimulus size (over 3°; see refs. 6, 7), resulting in surprisingly good color naming (8–11). The origin of such red–green residual activity remains unknown and is open to several explanations (7, 10, 12, 13). Other research has shown that protanopes and deuteranopes also exhibit minor alterations in the performance of the achromatic and yellow–blue mechanisms (see figures 4 and 5 in ref. 14). These functional alterations in red–green dichromacy also affect color naming: Moreira et al. (15) have developed a model that explains 94% of the color-naming variance in protanopes and 96% of that in deuteranopes. The color naming of dichromats suggests that, at least in some circumstances, dichromat color perception is supported by red–green residual activity (R–G_res), in addition to yellow–blue and achromatic mechanisms (modeled as s′ and L*_T in ref. 15). These mechanisms also might be relevant for other aspects of dichromats’ color perception, such as color preference.Although there has been much research on dichromats, their affective response to color has not been systematically investigated previously. Some visual simulations of how different stimuli appear to dichromats (16) have been demonstrated to work reasonably well (17). For example, these simulations suggest that some hues that appear reddish to common observers would appear desaturated and brownish for dichromats—a hue that normal trichromats typically dislike (18). Do dichromats also dislike a brownish appearance? Alternatively, if dichromats perceive a brownish appearance more commonly than trichromats, does this increased perception alter their preference for that appearance relative to other hues? Could dichromats’ and trichromats’ color preferences, like naming, be surprisingly similar if a residual red–green mechanism feeds into dichromats’ color preference?Investigating color preference in dichromats may provide insight into how they perceive color and also may shed light on the origins of color preference and inform ways to test further theories and models of color preference. Decades of color research have indicated a systematic pattern of preference in trichromats: Blue hues are commonly preferred, and yellow–green hues are commonly disliked (18–20). This pattern has been so systematic across studies that some have claimed it is universal, although others have pointed out that cross-cultural differences in color preference can be found also (21). Patterns of color preference have been explained in terms of the emotional response to color (22) and in terms of the valence of objects associated with colors (18).Another theory is that color preferences can be summarized in terms of the cone contrast between a color and its background (19). Supporting this theory, around 70% of the variance in preference across a set of hues could be explained by L−M and S−(L+M) cone contrasts for British and Chinese trichromats (19). However, other studies have failed to account for this much of the variance with cone contrasts alone (18, 21). Palmer and Schloss (18) extended the model, adding achromatic contrast and saturation as predictors, but accounted for only 37% of the variance. If the cone-contrast model works, we should find altered patterns of color preference in dichromats that reflect their altered color vision. If so, we should be able to model dichromat color preference, as Moreira et al. (15) did for color naming, using a model tailored for dichromats’ altered cone-opponent mechanisms.The current study investigates color preference in male dichromat (protanopes and deuteranopes) and trichromat observers (males and females). Color preference was measured for a set of 24 colors from the Berkeley Color Project (BCP) (18), comprising saturated, light, and dark versions of eight hues used in prior studies of trichromat color preference (18, 20, 21) and also the focal colors of the basic color categories (Fig. S1). The type of dichromacy was confirmed through the use of a set of color-vision tests including the Nagel anomaloscope. Observers rated their preference for the colors twice and also named the colors. Color preferences were compared across groups. To test the cone-contrast model, trichromat color preferences were modeled with trichromat cone contrasts as in Hurlbert and Ling (19). Dichromat color preferences then were modeled with cone contrasts that take into account dichromats’ altered cone responses. In addition, we explore the relationship between color naming and color preference in dichromats and trichromats, investigating whether color categorization, accuracy, speed, and consistency of naming predict how much a color is preferred.Open in a separate windowFig. S1.Thirty-five stimuli from the saturated (S), light (L), dark (D), and focal (F) sets presented against the background used in the experiment. Colors are only an approximation of those in the experiment because of reproduction inaccuracies.     

Evaluation of Color and Spectral Behavior of a Novel Flowable Resin Composite after Water Aging: An In Vitro Study

Background: This study aimed to evaluate the color matching, light transmittance, and reflectance characteristics of the novel flowable resin composite OCF-001 (OCF). Methods: Fifty-four resin composite molds were made with simulated class I cavities of A2, A3, and A4 shades by filling the rubber mold interspace with Estelite Sigma Quick (ESQ), Gracefil Putty (GP) and Filtek Supremme Ultra (FSU). After applying the adhesive, three different flowable resin composites (n = 6), OCF, Gracefil LoFlo (GLF), and Supreme Ultra Flowable (SUF), were used to fill the cavities. A colorimeter was used to measure the color parameters (CIEDE2000). The color measurements were taken immediately and after 28 days. Data were analyzed using the nonparametric Kruskal–Wallis (α = 0.05) and Wilcoxon tests. The light transmittance and reflection characteristics were measured with a black background using a spectrophotometer under D65 illumination. Results: The ΔE₀₀, and ΔC of OCF was lower than other tested materials in A2 and A3 shades both immediately and after 28 days. OCF showed the highest transmittance characteristic, and a relatively stable reflectance curve in all the wavelengths. Conclusions: OCF showed better shade matching with the surrounding shades of A2 and A3, a relative uniform reflectance and higher light transmission properties.     

Problems and pitfalls in the performance and interpretation of color Doppler flow imaging: observations based on the influences of technical and physiological factors on the color Doppler examination of mitral regurgitation

Color Doppler flow imaging has become an integral part of the echocardiographic examination. By providing real-time, two-dimensional spatial maps of normal and abnormal cardiac blood flows, this technique provides important information that may be used to guide patient management. The acquisition and display of color Doppler flow information may be influenced by technical factors, by the physiological condition of the patient, by abnormalities of cardiac morphology, and, on occasion, by artifact. In this article, the results of a study performed to evaluate the influence of technical factors on the color Doppler assessment of mitral regurgitation are reported. Mitral regurgitation jet area size changed significantly with variation in the control settings for color gain, color process, color map, color image resolution, and sector width. A review of those factors that influence the performance and interpretation of the color Doppler flow examination is provided and their significance discussed.     

Assessment of Ebstein's Anomaly and Its Surgical Repair Using Transesophageal Two-Dimensional Echocardiography and Doppler Color Flow Mapping

Transthoracic echocardiography is generally accepted as the procedure of choice for diagnosing Eb-stein's anomaly; however, an optimal evaluation is not always possible due to technical limitations. We have reported the utility of transesophageal echocardiography and Doppler color flow mapping in this condition, particularly for demonstrating structures and flow patterns in the atria and right ventricle. We conclude that in the evaluation of Ebstein's anomaly, these two echocardiography techniques are complementary and together can provide an excellent anatomical and functional assessment. (ECHOCARDIOGRAPHY, Volume 8, May 1991)     

Combined femoral pseudoaneurysm and arteriovenous fistula: diagnosis by Doppler color flow mapping

This case report is the first to describe a combined femoral pseudoaneurysm and arteriovenous fistula resulting from a cardiac catheterization, diagnosed by color Doppler.     

Combined Femoral Pseudoaneurysm and Arteriovenous Fistula: Diagnosis by Doppler Color Flow Mapping

This case report is the first to describe a combined femoral pseudoaneurysm and arteriovenous fistula resulting from a cardiac catheterization, diagnosed by color Doppler.     

World Color Survey color naming reveals universal motifs and their within-language diversity

We analyzed the color terms in the World Color Survey (WCS) (www.icsi.berkeley.edu/wcs/), a large color-naming database obtained from informants of mostly unwritten languages spoken in preindustrialized cultures that have had limited contact with modern, industrialized society. The color naming idiolects of 2,367 WCS informants fall into three to six “motifs,” where each motif is a different color-naming system based on a subset of a universal glossary of 11 color terms. These motifs are universal in that they occur worldwide, with some individual variation, in completely unrelated languages. Strikingly, these few motifs are distributed across the WCS informants in such a way that multiple motifs occur in most languages. Thus, the culture a speaker comes from does not completely determine how he or she will use color terms. An analysis of the modern patterns of motif usage in the WCS languages, based on the assumption that they reflect historical patterns of color term evolution, suggests that color lexicons have changed over time in a complex but orderly way. The worldwide distribution of the motifs and the cooccurrence of multiple motifs within languages suggest that universal processes control the naming of colors.     

Intraventricular Systolic Flow Mapping in Hypertrophic Cardiomyopathy

Ninety-two consecutive patients with hypertrophic cardiomyopathy were studied with pulsed and continuous-wave Doppler and color flow imaging to assess the intraventricular systolic flow profile from apex to base and compare it with that obtained in normals and in patients with aortic stenosis and systemic hypertension. Hypertrophic cardiomyopathy patients had higher intraventricular blood flow velocities (cm/sec) from apex to base compared with normals and aortic stenosis and systemic hypertension patients (apex: 41.5 ± 17.3 vs 24 ± 1.9,26.1 ± 2.9, and 26.4 ± 3.3; papillary muscles: 95.4 ± 66.5 vs 41.9 ± 4.9, 46.2 ± 3.4, and 46.4 ± 5.7; outflow tract: 249.3 ± 176.2 vs 66.9 ± 8.4, 64.1 ± 10.8, and 66 ± 9.5, respectively) (P < 0.001). Eighty-six (93%) hypertrophic cardiomyopathy patients showed an abnormal intraventricular systolic color flow pattern at one or more sites but none of the patients with aortic stenosis or systemic hypertension or normal controls. Of those, 65 (71%) showed one or more variant (mosaic) flow, all of whom had intraventricular gradients, while 75 showed abnormal aliased flow at a site other than the subaortic area. It is concluded that patients with hypertrophic cardiomyopathy often exhibit an abnormal spatial distribution of the intraventricular systolic flow velocity profile compared with normals and patients with secondary forms of ventricular hypertrophy that can readily be recognized with color flow imaging. This could improve the sometimes difficult separation of hypertrophic cardiomyopathy patients from secondary hypertrophy.     

Color superposition: a new modality for contrast echocardiography

Summary To improve the estimation of endocardial borders in echocardiography, a technique has been developed to combine images from contrasted and noncontrasted echocardiograms of the same heart-phase using a color superposition mode. This method allows both experienced as well as less experienced examiners to define the endocardial borders more reproducibly and objectively. This is achieved by displaying tissue structures as gray level images while the ventricular cavity is marked selectively by the color display of the contrast material zone.Results of volume estimations of the left ventricle by different examiners using several imaging modes including color superposition display are presented.     

Lateralization of categorical perception of color changes with color term acquisition

Categorical perception (CP) of color is the faster and more accurate discrimination of two colors from different categories than two colors from the same category, even when same- and different-category chromatic separations are equated. In adults, color CP is lateralized to the left hemisphere (LH), whereas in infants, it is lateralized to the right hemisphere (RH). There is evidence that the LH bias in color CP in adults is due to the influence of color terms in the LH. Here we show that the RH to LH switch in color CP occurs when the words that distinguish the relevant category boundary are learned. A colored target was shown in either the left- or right-visual field on either the same- or different-category background, with equal hue separation for both conditions. The time to initiate an eye movement toward the target from central fixation at target onset was recorded. Color naming and comprehension was assessed. Toddlers were faster at detecting targets on different- than same-category backgrounds and the extent of CP did not vary with level of color term knowledge. However, for toddlers who knew the relevant color terms, the category effect was found only for targets in the RVF (LH), whereas for toddlers learning the color terms, the category effect was found only for targets in the LVF (RH). The findings suggest that lateralization of color CP changes with color term acquisition, and provide evidence for the influence of language on the functional organization of the brain.     

Pitfalls in the color Doppler diagnosis of valvular regurgitation

Color Doppler flow mapping of the regurgitant jet is frequently used as a means of assessing the severity of valvular regurgitation. Although convenient, this method of assessing valvular regurgitation is subject to a number of hemodynamic and technical factors that may limit its accuracy. Variations in hemodynamic and structural factors such as orifice size, jet geometry, receiving chamber constraints, afterload, fluid viscosity, heart rate, and cardiac output may have profound effects on the measured regurgitant jet area. Variations in scanning and machine factors, such as scanning direction, Doppler angle, frame rate, color display algorithms, pulse repetition frequency (PRF), system gain, packet size, carrier frequency, wall filter, and transmit power have been shown to alter the measured regurgitant jet area significantly. Despite these limitations, color flow Doppler provides a relatively reliable noninvasive method for semiquantitative assessment of valvular regurgitation. Obviously, standardization of the design and application of the various available color mapping algorithms, as well as other machine and hemodynamic factors, would help provide more reliable and reproducible quantitative information about the degree of valvular insufficiency.     

Pigment Penetration Characterization of Colored Boundaries in Powder-Based Color 3D Printing

Color 3D printing has widely affected our daily lives; therefore, its precise control is essential for aesthetics and performance. In this study, four unique test plates were printed using powder-based full-color 3D printing as an example; moreover, the corresponding pigment-penetration depth, chromaticity value and image-based metrics were measured to investigate the lateral pigment penetration characteristics and relative surface-color reproduction of each color patch, and to perform an objective analysis with specific microscopic images. The results show that the lateral pigment-penetration depth correlates with the number of printed layers on the designed 3D test plates, and the qualitative analysis of microscopic images can explain the change in chromaticity well. Meanwhile, there is an obvious linear correlation between the mean structural similarity, color-image difference and color difference for current color samples. Thus, our proposed approach has a good practicality for powder-based color 3D printing, and can provide new insight into predicting the color-presentation efficiency of color 3D-printed substrates by the abovementioned objective metrics.     

Color Flow Identification of Multiple Ventricular Septal Defects in a Patient with Elevated Pulmonary Vascular Resistance

A 12-year-old boy with a large ventricular septal defect and elevated pulmonary vascular resistance had surgical closure of his defect. There was a gradual diminution in pulmonary resistance over a 2-week period. On the twelfth postoperative day, a new systolic murmur was noted, and an additional small muscular ventricular septal defect was diagnosed by color flow Doppler echocardiography. This defect had not been seen on preoperative left ventricular angiography, nor on several postoperative echocardiography studies. The fall in this patient's pulmonary vascular resistance was analogous to the hemodynamic changes typical of a newborn infant. In that context, the timing of the clinical and echocardiographic appearance of the ventricular septal defect is discussed. (ECHOCARDIOGRAPHY, Volume 8, May 1991)     

An Attempt to Analyze Color Wavelengths with an Electronic Endoscope

We attempted to measure the dominant wavelengths of gastric mucosal lesions and to extract and present color differences of the lesions in image form, by converting spectroscopic visual signals (composed of red, green and blue components) obtained from an electronic endoscope into digital color files. The dominant wavelength, as measured from signals input without gamma correction, was significantly shorter in gastric mucosa affected by atrophic gastritis and type lie early gastric cancer than in normal mucosa. This analysis revealed a significant difference in dominant wavelengths between the endoscopically normal mucosa of the stomach and that found to have been affected by early gastric carcinoma and atrophic gastritis. Color difference extraction allowed us to make a morphological characterization of the surface of type lie early gastric cancer, although this was possible in only one case. The results of this study suggest the diagnostic value of digital representation of the mucosal surface features provided by endoscopy. It is suggested that, in the future, analog endoscopic diagnosis will be replaced by digital endoscopic diagnosis and computerized endoscopic diagnosis.     

Seeing the light: illumination as a contextual cue to color choice behavior in bumblebees

The principal challenge faced by any color vision system is to contend with the inherent ambiguity of stimulus information, which represents the interaction between multiple attributes of the world (e.g., object reflectance and illumination). How natural systems deal with this problem is not known, although traditional hypotheses are predicated on the idea that vision represents object reflectance accurately by discounting early in processing the conflating effects of illumination. Here, we test the merits of this general supposition by confronting bumblebees (Bombus terrestris) with a color discrimination task that can be solved only if information about the illuminant is not discounted but maintained in processing and thus available to higher-order learned behavior. We show that bees correctly use the intensity and chromaticity of illumination as a contextual cue to guide them to different target colors. In fact, we trained bees to choose opposite, rather than most similar, target colors after an illumination change. This performance cannot be explained with a simple color-constancy mechanism that discounts illumination. Further tests show that bees do not use a simple assessment of the overhead illumination, but that they assess the spectral relationships between a floral target and its background. These results demonstrate that bees can be color-constant without discounting the illuminant; that, in fact, they can use information about the illuminant itself as a salient source of information.